I have over 1 year of experience working in computer vision. Currently, I work as Software Engineer improving products and services for our customers by using retail analytics, standing up big-data analytical tools, creating and maintaining models, and onboarding compelling new data sets.

Previously, I was Computer Vision Intern at The Spark Foundation, where I got experience about analyzation of vision data from different open-source platforms i.e. (kaggle, google images, openimages etc.) and to train different deep learning models on that data.

Recent projects I have worked on includes,

• custom retraining of different deeplearning models with nvidia transfer learning toolkit.
• run new deep learning models(i.e. yolov5, ssd) on axis-communication smart cameras (embedded devices).
• worked on nvidia deepstream sdk, for development of some custom applications.
• run yolov5 pytorch-model with c++/python.
• found new pros and cons inside transfer learning toolkit while retraining custom models.
• developed desktop application like video player for object tracking in (C#)
• developed a window services for object counting and for some other applications in (C++-Console)

Currently, I am working on different tracking problem like smart counting, multiple ids reallocation, same id tracks joining etc.

Competencies: computer vision, machine learning, deep learning, object detection, image classification, object segmentation, non maximum suppression, object tracking, Python, C++, C#, docker, .NET framework.

Hobbies: programming, thinking about new ideas and playing software games.